Review of Mendelian Randomization Studies on Endometrial Cancer

被引:13
|
作者
Guo, Jian-Zeng [1 ,2 ]
Wu, Qi-Jun [1 ,2 ,3 ]
Liu, Fang-Hua [1 ,3 ]
Gao, Chang [1 ,3 ]
Gong, Ting-Ting [2 ]
Li, Gang [4 ]
机构
[1] China Med Univ, Shengjing Hosp, Dept Clin Epidemiol, Shenyang, Peoples R China
[2] China Med Univ, Shengjing Hosp, Dept Obstet & Gynecol, Shenyang, Peoples R China
[3] China Med Univ, Shengjing Hosp, Clin Res Ctr, Shenyang, Peoples R China
[4] China Med Univ, Shengjing Hosp, Dept Ultrasound, Shenyang, Peoples R China
来源
基金
中国国家自然科学基金;
关键词
causality; instrumental variables; Mendelian randomization; endometrial cancer; risk factors; DOSE-RESPONSE METAANALYSIS; POLYCYSTIC-OVARY-SYNDROME; SEX STEROID-HORMONES; TELOMERE LENGTH; BREAST-CANCER; EPIDEMIOLOGIC EVIDENCE; MOLECULAR-MECHANISMS; CAUSAL INFERENCE; RISK-FACTOR; OBESITY;
D O I
10.3389/fendo.2022.783150
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Endometrial cancer (EC) is a common gynecological cancer. In some parts of the world, the incidence and mortality of EC are on the rise. Understanding the risk factors of EC is necessary to prevent the occurrence of this disease. Observational studies have revealed the association between certain modifiable environmental risk factors and EC risk. However, due to unmeasured confounding, measurement errors, and reverse causality, observational studies sometimes have limited ability to judge robust causal inferences. In recent years, Mendelian randomization (MR) analysis has received extensive attention, providing valuable insights for cancer-related research, and is expected to identify potential therapeutic interventions. In MR analysis, genetic variation (alleles are randomly assigned during meiosis and are usually independent of environmental or lifestyle factors) is used instead of modifiable exposure to study the relationship between risk factors and disease. Therefore, MR analysis can make causal inference about exposure and disease risk. This review briefly describes the key principles and assumptions of MR analysis; summarizes published MR studies on EC; focuses on the correlation between different risk factors and EC risks; and discusses the application of MR methods in EC research. The results of MR studies on EC showed that type 2 diabetes, uterine fibroids, higher body mass index, higher plasminogen activator inhibitor-1 (PAI-1), higher fasting insulin, early insulin secretion, longer telomere length, higher testosterone and higher plasma cortisol levels are associated with increased risk of EC. In contrast, later age of menarche, higher circulatory tumor necrosis factor, higher low-density lipoprotein cholesterol, and higher sex hormone-binding globulin levels are associated with reduced risk of EC. In general, despite some limitations, MR analysis still provides an effective way to explore the causal relationship between different risk factors and EC.
引用
收藏
页数:15
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